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Record W6986282470

The Peaks and Valleys of Connection – Lessons from Smart Village Initiatives and Supportive Policies in the EU and UK for a Canadian Context

2023· dissertation· en· W6986282470 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2023
Typedissertation
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Citizen journalismGovernment (linguistics)Rural developmentEuropean unionPolicy developmentRural area
DOInot available

Abstract

fetched live from OpenAlex

Limited by an incoherent government policy regime towards rural connectivity and development, rural communities across Canada, especially in mountainous regions, struggle to access and implement innovative technologies and strategies to address local development needs. Meanwhile, The European Union (EU) and United Kingdom (UK) have begun to experiment with Smart Village policy and pilot projects. Using a mixed methods approach, this research investigates how the Smart Village approach has been employed in the EU and UK to support rural development in mountainous regions. The research findings are a culmination of a content analysis of EU and UK rural development policies and a case study of Smart Village initiatives in the Scottish Highlands and Uplands. Research findings demonstrate the intersection of geography, technology, and policy in rural development, providing several transferable lessons for Canadian policy makers and mountainous communities seeking enhance development outcomes through place and participatory based strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.820

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0340.021
Scholarly communication0.0150.004
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.269
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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